What is the definition of rationality?
When we use the term rationality in AI, it tends to conform to the game theory/decision theory definition of rational agent. 

In a solved or tractable game, an agent can have perfect rationality.  If the game is intractable, rationality is necessarily bounded. (Here, "game" can be taken to mean any problem.)

There is also the issue of imperfect information and incomplete information.  

Rationality isn't restricted to objectively optimal decisions but includes subjectively optimal decisions, where the the optimality can only be presumed.  (That's why defection is the optimal strategy in 1-shot Prisoner's Dilemma, where the agents don't know the decisionmaking process of the the competitor.)  


Rationality here conforms to Russell &amp; Norvig's definition, where it is related to performance in an environment. 


What may be rational in one environment may not be rational in a different environment.  Additionally, what may be locally rational for a simple reflex agent will not appear rational from the perspective of an agent with more knowledge, or a learning agent. 

Iterated Dilemmas, where there is communication in the form of prior choices, may provide an analogy.  An agent that always defects, even where the competitor has shown willingness to cooperate, may not be regarded as rational because  defecting vs. a cooperative agent does not maximize utility.  A simple reflex agent wouldn't have the capacity to alter its strategy.

However, rationality used in the most general sense might allow that, to the agent making the decision, if the decision is based on achieving an objective, and the decision is reached utilizing the information available to that agent, the decision is may be regarded as rational, regardless of actual optimality.